SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 2751–2775 of 3304 papers

TitleStatusHype
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
PixelHop: A Successive Subspace Learning (SSL) Method for Object ClassificationCode0
Speeding up astrochemical reaction networks with autoencoders and neural ODEsCode0
Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMsCode0
Image Similarity using An Ensemble of Context-Sensitive ModelsCode0
Image Super-resolution via Feature-augmented Random ForestCode0
Completing partial recipes using item-based collaborative filtering to recommend ingredientsCode0
PLPCA: Persistent Laplacian Enhanced-PCA for Microarray Data AnalysisCode0
Model Reduction of Linear Dynamical Systems via Balancing for Bayesian InferenceCode0
Bayesian Non-linear Latent Variable Modeling via Random Fourier FeaturesCode0
Modified Genetic Algorithm for Feature Selection and Hyper Parameter Optimization: Case of XGBoost in Spam PredictionCode0
Detecting Adversarial Examples through Nonlinear Dimensionality ReductionCode0
Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate DataCode0
Encoding large information structures in linear algebra and statistical modelsCode0
Manifold Fitting under Unbounded NoiseCode0
Spherical Rotation Dimension Reduction with Geometric Loss FunctionsCode0
A Grid-based Method for Removing Overlaps of Dimensionality Reduction Scatterplot LayoutsCode0
Bayesian Non-stationary Linear Bandits for Large-Scale Recommender SystemsCode0
Designing Illuminant Spectral Power Distributions for Surface ClassificationCode0
Spherinator and HiPSter: Representation Learning for Unbiased Knowledge Discovery from SimulationsCode0
Linear and Quadratic Discriminant Analysis: TutorialCode0
Positive semi-definite embedding for dimensionality reduction and out-of-sample extensionsCode0
Tracking the topology of neural manifolds across populationsCode0
Distributed Lyapunov Functions for Nonlinear NetworksCode0
Derivative-enhanced Deep Operator NetworkCode0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified